https://github.com/davydantoniuk/winstars-data-science
An object-oriented approach to MNIST classification and an ML pipeline integrating Named Entity Recognition (NER) with animal image classification.
https://github.com/davydantoniuk/winstars-data-science
Last synced: 4 months ago
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An object-oriented approach to MNIST classification and an ML pipeline integrating Named Entity Recognition (NER) with animal image classification.
- Host: GitHub
- URL: https://github.com/davydantoniuk/winstars-data-science
- Owner: davydantoniuk
- Created: 2025-02-18T12:52:46.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-22T09:33:34.000Z (4 months ago)
- Last Synced: 2025-02-22T10:26:51.127Z (4 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 2.28 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Winstars AI DS Internship Test
This repository contains two tasks focused on Machine Learning, Computer Vision, and NLP:
- `Task 1`: Implementing multiple classification models on the MNIST dataset using an object-oriented approach.
- `Task 2`: Building an ML pipeline that integrates Named Entity Recognition (NER) with image classification.
Each task is structured into separate folders with clear documentation, well-commented code, and Jupyter Notebook demonstrations.